Research on intellectual property protection algorithm of deep semantic segmentation model

In its judicial interpretation, the Supreme People's Court clarified that algorithmic information can be protected by trade secrets by way of enumeration, which reflects the increased importance of algorithmic trade secret protection. Deep models have high intellectual property value and commercial value, and have even become the core competitiveness of some individuals or small businesses, making them the target of attacks by some malicious competitors and lawless elements. Current digital watermarking technology has been extended to deep neural networks, but these methods are only suitable for protecting the intellectual property of classification models. Therefore, this article proposes research on the intellectual property protection of semantic segmentation models. This paper abandons the traditional method of selecting trigger sets in classification model protection, and proposes an adversarial generation method to independently design trigger sets, embed patterns or symbols with special markings into pictures, and then use a backdoor mechanism to embed trigger set digital watermarks into semantic segmentation In the model, the backdoor disadvantages of the model are converted into backdoor advantages, making the segmentation model more discriminative during the verification process.